sequential simulation of integrated hydropower releases...

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22 AMSE JOURNALS –2014-Series: Modelling C; Vol. 75; N° 1; pp 22-44 Submitted Jan. 2014; Revised June 20, 2014; Accepted July 15, 2014 Sequential Simulation of Integrated Hydropower Releases: Case Study of Ero-Omola Falls, Kwara State, Nigeria. *B.F. Sule, **A.O. Ogunlela and ***K. M. Lawal *Director, National Centre for Hydropower Research and Development, University of Ilorin, Ilorin, Nigeria. **Agricultural and BioSystems Engineering Department, University of Ilorin, Ilorin, Nigeria ***Catchment Director, Nigeria Integrated Water Resources Management Commission, Abuja, Nigeria. ([email protected]) Abstract: The sequent peak algorithm and sequential streamflow routing technique were used to simulate integrated development of Ero-Omola Falls, for hydropower, water supply, irrigation and flood control. The analysis indicated hydropower releases of 21m 3 /s, municipal water supply of 0.538m 3 /s, irrigation water supply of 0.24m 3 /s and ecological water releases of 1.6 x 10 -3 m 3 /s. The result shows that the entire reservoir was drafted effectively for hydropower generation with minimal hydraulic losses of about 1.83m 3 /s. The simulation result indicated about 20.6% more potential hydropower, while additional 23.4% annual energy could be generated. The computed net head routed through the usable discharge falls within the minimum range of head and discharge respectively for a cross-flow turbine recommended for the scheme. The results established that conjunctive use of hydropower releases is an effective mitigation measures against seasonal flooding downstream of power plant in addition to allowing for withdrawal for other uses such as water supply and irrigation. Keywords: Integrated Hydropower Development, Sequential Routing, Simulation, 1. Introduction Sequential simulation analysis of streamflow associated with hydropower is of paramount importance in the planning, design and operation of water resources development project. In order to design and construct hydroelectric systems, the analysis of the system (runoff or reservoirs and power plants) operations over a representative hydrologic period is required (Zolgay and Stedinger, 1991). This may be done by using mathematical simulation for analysis of hydropower

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Page 1: Sequential Simulation of Integrated Hydropower Releases ...amsemodelling.com/publications/modelling... · Sequential Stream flow Routing (SSR) is a common method for assessing energy

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AMSE JOURNALS –2014-Series: Modelling C; Vol. 75; N° 1; pp 22-44

Submitted Jan. 2014; Revised June 20, 2014; Accepted July 15, 2014

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Sequential Simulation of Integrated Hydropower Releases: Case Study of Ero-Omola Falls, Kwara State, Nigeria.

*B.F. Sule, **A.O. Ogunlela and ***K. M. Lawal

*Director, National Centre for Hydropower Research and Development, University of Ilorin,

Ilorin, Nigeria. **Agricultural and BioSystems Engineering Department, University of Ilorin, Ilorin, Nigeria

***Catchment Director, Nigeria Integrated Water Resources Management Commission, Abuja, Nigeria.

([email protected]) Abstract: The sequent peak algorithm and sequential streamflow routing technique were used to

simulate integrated development of Ero-Omola Falls, for hydropower, water supply, irrigation and

flood control. The analysis indicated hydropower releases of 21m3/s, municipal water supply of

0.538m3/s, irrigation water supply of 0.24m3/s and ecological water releases of 1.6 x 10-3m3/s. The

result shows that the entire reservoir was drafted effectively for hydropower generation with

minimal hydraulic losses of about 1.83m3/s. The simulation result indicated about 20.6% more

potential hydropower, while additional 23.4% annual energy could be generated. The computed net

head routed through the usable discharge falls within the minimum range of head and discharge

respectively for a cross-flow turbine recommended for the scheme. The results established that

conjunctive use of hydropower releases is an effective mitigation measures against seasonal

flooding downstream of power plant in addition to allowing for withdrawal for other uses such as

water supply and irrigation.

Keywords: Integrated Hydropower Development, Sequential Routing, Simulation,

1. Introduction Sequential simulation analysis of streamflow associated with hydropower is of paramount

importance in the planning, design and operation of water resources development project. In order

to design and construct hydroelectric systems, the analysis of the system (runoff or reservoirs and

power plants) operations over a representative hydrologic period is required (Zolgay and

Stedinger, 1991). This may be done by using mathematical simulation for analysis of hydropower

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reservoir systems. Descriptive simulation models due to their computational advantages are able to

consider more details of real systems than optimization model (Kelman, 1980). Sequential Stream

flow Routing (SSR) is a common method for assessing energy potential in practical hydropower

projects design and operation in most part of the world (Labaide, 2004). The quality and accuracy

of hydrologic and hydraulic analysis can govern the project feasibility and engineering design to a

great extent. The most common hydraulic parameters of interest to engineers are the temporal and

spatial distribution of depth and velocity of various discharges. Methods for determining these

parameters vary considerably depending on the complexity of the flow pattern, time and budget

limitations, data availability, applications of results, available equipment, etc. The general practice

has been to use one dimensional steady state algorithms for flurial streams and two dimensional

unsteady state models for lakes, reservoirs and coastal projects (Koch-Guibert, 1985). The

diversity of hydro project provides engineers with a range of challenging hydrodynamic problems

such as flood routing in rivers, flood plain hydraulics, urban storm drainages, circulation in lakes

and reservoir that must be dealt with. While all of these are basically three dimensional flow

problems, some of them may be approximated adequately either by one–dimensional or two

dimensional mathematical models. Numerical flows simulation plays an important role in

optimization of the hydraulic turbines and other components of a hydropower plant. The roles

include:

a) Prediction of power output of turbine

b) Achievement of maximum hydraulic efficiency

c) avoiding penstock cavitation

d) minimizing plant vibration

Beard and Kumar (1999) re-appraised the efficiency of Sequential Stream flow Routing (SSR)

technique with optimization of reservoir inflow to meeting energy demand of Chatawa reservoir in

Nepal. They reported that SSR is an acceptable method for assessing energy potential in practical

hydropower projects designs and operations. In order to simulate sequential releases an iterative

single period linear programming (LP) model was utilized. The linear programming model

minimizes the sum of reservoir releases and maximizes the sum of reservoir storages. Reservoir

optimization for hydropower, irrigation & municipal water supply was simulated by Hingis et al

(2001) where maximization of energy output was considered as the objective function, while

reservoir characteristics, the irrigation requirements, water supply and ecological needs were

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included in the constraints. Beard (1982) utilized Monte Carlo technique to extract maximum

degree of pertinent information from monthly stream flow data and generated values whose

statistical characteristics were consistent with the observed monthly stream flow data. Nash (1984)

deployed hourly rainfall of annual storms to develop a non linear mathematical model to represent

the stochastic process of the hourly rainfalls in which the random variables denote trend

components of various functions. It was found that the non-stationary Markov chain model is

consistently satisfactory and most practical for the purpose. Analysis of low flow series were also

reported by Jensens (1998) where the low flows in m3/s were arranged in decreasing order of

magnitude and were ranked accordingly using the Weibul algorithms. It is widely believed that

reservoir operations policy alone may not guarantee security against seasonal flooding. The

formulation of sustainable conjunctive use of hydropower releases is the best mitigation measures

against seasonal flooding of farmland downstream of the dam. Conjunctive use of hydropower

releases involves provision of fish passes, water supply facility, irrigation and drainages as well as

ecological water balance for downstream eco-systems (IHA, 2007). It has also proved to be the

most effective and most sustainable ways of controlling flood since almost 90% of releases would

be diverted for useful purposes. The conjunctive use of hydropower releases also ensures that

economic activities of benefitting communities are not disconnected by developmental projects

(IHA, 2004).

1. Study Approach and Methodology

Accumulation of reliable hydrological data for hydropower development projects demands

intelligent and painstaking endeavour and continuous effort. Inadequate water availability has

contributed significantly to low capacity utilization and failure of most hydropower plants in

Nigeria (Umolu, 2006). Over optimism and conclusions based on insufficient and inaccurate

streamflow data are common and are sources of economic waste to government. Over or under

estimation of runoff for hydropower projects are frequently reflected in the inability to operate the

plants at full capacity soon after completion. The problem is compounded by the occurrence of

climatic cycle which cannot as yet be predicted with precision, together with wide variation of

precipitation and streamflow from season to season. This study was carried out in three stages.

These are (a) development of monthly flow rating equations, (b) extension of streamflow data, and

(d) sequent peak analysis and simulation.

The study area is located along Osi- Isolo-Ajuba Road off Osi-Idofin road in Oke-Ero LGA,

Kwara State of Nigeria. It is about 116 km from Ilorin the state capital. The height of the fall is

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about 59.01m high. The catchment area of Ero-Omola-Falls is about 145km2 with contribution from

two rivers namely, Ero-river from Iddo- Faboro near Ifaki in Ekiti State and Odo-Otun river from

Ajuba. Ero-Omola Falls lies between Latitude North N080 09’ 34.6” and N080 09’ 30.8” and between

Longitude East E 050 14’ 07.4” and E 050 14’ 06.7”. Figure 1 shows map of Nigeria and the

location of the study area.

Figure 1: Project Location Map

2.1 Development of Monthly Flow Rating Equations from Streamflow Data

A staff gauge is the simplest device for measuring river stage or water surface elevation.

The staff gauge is a graduated self-illuminated strip of metal marked in metres and fractions

thereof. Water levels were read daily, recorded and collated on monthly basis at the gauging station

at Ero-Omola Falls from 2009 to 2011. Streamflow discharge measurement were taken several time

and used along with gauge heights, to develop the rating equations. In general for a gauge height H

(m); the discharge Q (m3/s) is related to height H (m) as (Punmia and Pande (2008) :

Q = K (H +/-Ho) n (1) When Ho=0, The rating equation is given as (Sharma, 1979)

• Kwara State Ilorin

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Q = K H n (2)

Where

Q = Discharge (m3/s)

H = Gauge Height (m)

Ho = Gauge Height when the flow is zero (m)

n and k are constants

This is a parabolic equation which plots as a straight line on double logarithmic graph sheet. K & n

are determined using the least square methods

2.2 Extension of Streamflow Data

One year stream flow data generated by the rating equation at Ero-Omola Falls, Kwara state,

was extended in order to fulfill other hydrological analysis requirement. In order to achieve this, the

model proposed by Thomas and Fierring in 1962 (McMachon and Mein, 1978) was adopted. The

model utilized Markov theory to represent actual stream flow when the monthly stream flow, qi, are

normally distributed and follow a first – order auto regressive model. The algorithm for the Thomas

and Fierring model is giving as Karamouz (2003):

( ) ( ) 2121,111,11 1 ++++++ −+−+= jjjijijjji rSZqqbqq (3)

( ) ( )( )2)1,()1(1,)1,()1(1 1 ++++++ −+−+= jjxjxiixijjxixi rskXbX µµ (4)

( ) ( )( )2)1,()1(1,)1,()1(1 1 ++++++ −+−+= jjxjxiixijjxixi rSkXbX µµ

where ii qX ln= ; qj = monthly flow (5)

2.3 Sequent Peak Algorithm

It is imperative to make provision for a reservoir due to three months break of inflow at

Ero-Omola during the dry season. This will allow the storage to provide the needed flow to the

turbines uninterrupted throughout the year. The capacity required for a reservoir depends upon the

inflow available and the demand. If the available inflow in the river is always greater than the

demand, there is no storage required. On the other hand, if the inflow in the river is small but the

demand is high, a large reservoir capacity is required. The required capacity for the reservoir at Ero-

Omola was evaluated using sequent peak algorithm. Linsely et al (1992) and Louck and Sigvaldson

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(2004) described the use of sequent peak algorithm stating that values of cumulative sum of inflow

minus withdrawal including average evaporation and seepage are calculated. The first peak local

maximum of cumulative net inflow and the sequent peak ( next following peak that is greater than

the first peak) are identified. The required storage for the interval is the difference between the

initial peak and the lowest trough in the interval. The process is repeated for all cases in the period

under study and the largest value of the required storage can be found.

2.4 Simulation The sequential stream flow routing method sequentially computes the energy output at a

specified interval in the period of analysis. A continuity equation is used to route the stream along

the natural channels, taking into account the variations in reservoir elevation as a result of the

inflow simulations. Use of the sequential routing in the continuity equations allows the simulation

of the hydropower, but also includes flood control operation, irrigation and water supply operation.

This system is based upon continuity equation given as:

(6)

Where AS=change in reservoir storage (m3)

I = Reservoir Inflow (m3)

O = Reservoir outflow (m3)

L = Sum of the losses due to evaporations, diversions, etc. (m3)

The sequential stream flow routing method can be applied to basically any type of flood analysis.

These include run-off-the river projects; run-off-the river project with pondage; flood control

project only; storage regulated for power only; and storage regulated for multi-purpose, including

power, peaking hydro-projects and pumped storage hydro-projects. The basic type of data needed

are the historical stream flows and other information from the flow duration analysis. The basic

steps for this procedure are (US Army Corps of Engineers, 1995):

Step 1-Select plant capacity

Step 2-Compute stream flow available for power generation

Step 3-Determine average pond elevation

Step 4- Compute net head

Step 5- Estimate efficiency

Step 6-Compute generation

Step 7-Compute Average Annual Energy

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To perform the routing, the continuity equation is expanded as:

∆S =I - (Qp +QL +QS) – (E +W) (7)

Where Qp =Power Discharge

QS =Overflow or spill

QL = Leakages or waste

E = Net Evaporation Losses (Evaporation –Precipitation)

W = Withdrawal for water supply, irrigation, recreation etc.

the rate of storage ∆S for a given time interval can be defined as;

(8)

Where St = beginning of period of storage

St+∆t = end of period of storage

∆t = is the storage or routing period (30days, 7days, 1day, 1hour)

Cs = Discharge to storage conversion factor

Substituting (8) in (7) and rearranging gives

St+∆t = St - Cs [I –Qp - QL-QS – (E +W)]

Or S2 = S1 - Cs[ (I –Qp - QL-QS –(E +W)] (9)

3. Results and discussion

3.1 Rating Equations and Streamflow Extension

The twelve rating equation developed using the recorded data on gauge heights and the

corresponding measured discharges between Januarys to December is presented below. The

discharge generated from the Rating equations is presented in Table 1, while the extended monthly

discharges from 2009-2017 are presented in Table 2.

Q = 9.206 H 0.491 (10)

Q = 9.253 H0.765 (11)

Q = 9.089 H0.934 (12)

Q = 10.496 H1.049 (13)

Q = 10.229 H1.455 (14)

Q = 8.539 H2.258 (15)

Q = 0.610 H7.789 (16)

Q = 12.65 H1.517 (17)

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Q = 25.308 H0.400 (18)

Q = 1.166 H5.505 (19)

Q = 17.167 H2.753 (20)

Q = 1.617 H5.977 (21)

Table 1: Ero-Omola daily discharge data generated from rating equations

Day Jan Feb Mar Apr May June July Aug Sept Oct Nov. Dec.

1 6.177 4.908 3.220 5.285 4.399 16.815 6.690 9.710 25.104 6.596 40.024 6.436

2 6.177 4.866 3.580 5.285 15.320 15.983 5.961 9.188 25.001 6.083 39.219 5.849

3 6.177 4.846 3.526 5.179 14.816 14.389 4.997 30.337 29.118 5.375 36.102 5.052

4 6.143 4.977 3.491 5.072 14.317 13.132 4.172 29.821 28.787 4.538 33.148 4.573

5 6.143 4.941 3.437 7.111 13.014 11.029 3.468 29.821 28.620 3.810 31.037 4.132

6 6.143 4.905 3.384 6.895 12.219 7.4255 2.692 28.546 28.280 9.363 29.013 3.538

7 6.143 4.887 3.313 6.572 9.785 6.563 2.072 27.040 27.131 8.352 26.449 3.017

8 6.143 4.869 3.259 6.464 9.639 5.916 1.474 26.298 27.131 7.144 26.139 1.347

9 6.143 4.832 3.187 6.464 9.493 5.305 3.258 24.113 28.704 6.083 24.623 1.117

10 6.143 4.260 3.134 6.356 9.932 4.872 2.692 22.928 28.451 5.155 23.452 0.920

11 6.143 4.225 3.845 6.141 9.348 13.878 1.811 21.995 28.194 4.161 15.342 0.656

12 6.143 4.172 3.736 6.034 8.917 13.378 1.375 21.303 28.021 3.563 14.058 0.530

13 6.143 4.119 3.626 5.927 8.492 12.408 0.376 19.275 27.492 2.900 12.074 0.395

14 6.143 4.084 3.535 5.713 8.352 11.252 0.318 16.051 32.646 2.285 12.074 0.289

15 6.110 4.013 3.205 5.392 7.937 10.589 0.318 15.431 32.438 2.071 11.700 0.246

16 6.110 4.959 3.187 5.179 7.527 6.563 0.097 12.078 32.087 0.931 10.974 0.208

17 6.110 4.814 3.152 7.653 9.932 5.916 0.064 11.331 30.845 0.879 30.353 0.147

18 6.110 4.704 3.718 7.328 9.639 7.971 19.479 0 30.466 0.781 27.712 0.102

19 6.110 4.365 3.827 6.356 9.348 7.073 12.262 0 30.000 0.576 25.831 3.926

20 6.110 4.209 3.736 6.249 8.917 6.316 9.891 9.710 29.604 0.446 22.880 3.183

21 6.110 4.030 3.663 8.305 8.352 20.068 6.316 8.846 29.604 4.161 15.786 1.433

22 6.110 4.866 3.590 8.087 8.213 18.549 4.997 8.677 30.234 3.810 14.478 1.266

23 6.110 4.783 3.498 9.836 7.937 17.670 3.690 8.677 29.843 3.329 13.241 1.117

24 6.110 4.741 3.442 9.288 7.799 16.535 2.364 8.342 29.684 2.900 11.700 0

25 6.110 4.699 3.294 8.741 7.527 15.174 1.580 24.353 29.282 2.639 10.278 0

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Months

2029

2030 2031

2032 2029

2030 2033

2034 2035

2036 2037

2038 January

6.857 6.884

6.911 6.938

6.857 6.884

6.965 6.993

7.020 7.048

7.075 7.020

February 7.458

8.172 8.954

9.811 7.458

8.172 10.750

11.778 12.903

14.137 15.487

12.903 M

arch 4.101

4.236 4.375

4.518 4.101

4.236 4.666

4.819 4.976

5.139 5.306

4.976 A

pril 25.500

26.430 27.393

28.391 25.500

26.430 29.425

30.498 31.609

32.760 33.953

31.609 M

ay 35.164

35.831 36.510

37.201 35.164

35.831 37.906

38.624 39.356

40.101 40.861

39.356 June

44.614 45.675

46.760 47.870

44.614 45.675

49.006 50.169

51.359 52.576

53.822 51.359

July 27.497

31.245 20.556

23.360 27.497

31.245 26.545

30.164 34.276

38.948 44.256

34.276 A

ugust 36.955

39.537 40.677

41.850 36.955

39.537 30.835

31.419 32.014

32.621 33.239

32.014 Septem

ber 53.537

54.184 54.839

55.501 53.537

54.184 56.172

56.851 57.538

58.233 58.936

57.538 O

ctober 36.533

37.405 38.298

39.211 36.533

37.405 40.145

41.101 42.080

43.081 44.106

42.080 N

ovember

52.576 53.822

36.738 37.615

52.576 53.822

38.512 39.430

40.370 41.331

42.315 40.370

Decem

ber 16.468

16.369 16.270

16.172 16.468

16.369 16.075

15.979 15.884

15.789 15.695

15.884

Table 2: Projected Mean M

onthly Streamflow

Dischages(m

3/s) Data For Ero-O

mola (2009-2038)

Months

2009 2010

2011 2012

2013 2014

2015 2016

2017 2018

2019 2020

2021 2022

2023 2024

2025 2026

2027 2028

January 6.049

6.074 6.100

6.125 6.150

6.176 6.201

6.226 6.252

6.278 6.303

6.329 6.355

6.381 6.407

6.433 6.459

6.485 6.511

6.537

February 4.939

3.610 3.957

4.338 4.755

3.475 3.810

4.177 4.578

5.018 5.500

6.028 6.606

4.827 3.528

3.868 4.240

4.648 5.094

5.583

March

3.755 3.423

3.122 2.847

2.597 3.001

3.465 4.001

4.618 4.209

3.837 3.498

3.189 2.909

2.654 2.421

2.504 2.589

2.677 2.767

April

12.840 12.223

11.635 11.076

10.544 10.038

10.405 10.786

11.1808 11.589

12.013 12.452

12.907 13.379

13.867 14.374

14.899 15.443

16.006 16.591

May

19.648 20.021

20.399 20.786

21.180 21.582

21.991 22.408

22.833 23.266

23.707 24.156

24.614 25.081

25.556 26.041

26.534 27.037

27.550 28.072

June 21.391

21.910 22.441

22.985 23.541

24.111 24.693

25.289 25.899

26.524 27.163

27.816 28.485

29.170 29.870

30.587 31.320

32.071 32.839

33.625

July 24.097

25.941 27.927

30.064 32.364

34.840 20.838

12.464 14.165

16.098 18.295

20.790 23.625

26.846 30.506

34.665 39.390

44.758 34.798

39.541

August

36.955 39.537

40.677 41.850

43.056 44.296

45.571 46.883

38.589 31.765

32.685 33.631

34.604 35.604

36.632 37.690

38.778 39.897

36.955 39.537

September

49.071 45.150

41.542 38.224

38.687 39.156

39.631 40.111

40.597 41.089

41.587 42.090

42.600 43.116

43.638 44.166

44.701 45.242

45.790 46.344

October

39.917 42.858

46.015 42.858

46.015 49.404

46.015 32.937

35.365 37.971

40.768 43.771

46.995 46.883

38.589 36.632

37.690 38.778

39.897 36.955

Novem

ber 32.307

33.242 34.204

35.193 36.210

37.256 38.331

39.437 40.575

41.745 42.948

44.185 45.458

46.766 48.112

37.126 33.425

37.838 38.741

39.664

Decem

ber 19.979

19.852 19.725

19.600 19.475

19.352 19.230

19.108 18.988

18.868 18.750

18.632 18.515

18.400 18.285

18.171 18.058

17.946 17.835

17.724

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3.2 Reservoir Elevation - Storage Computation

The reservoir elevation - storage computation is presented in Table 3 and the elevation – capacity and elevation – area curves are given in Figure 2.

Table 3: Reservoir Elevation Storage Computation

Contour Area Enclosed

Average Area

Height Between Contour

Volume Between Contour

Volume Up to Contour

m2 (103) m2 (103) m. m3 m3 (106) 450 0 0

451 2.4 1.2 1 1.2 1.2

452 7.9 3.95 1 3.95 5.15

453 35 17.5 1 17.5 22.65

454 57 28.5 1 28.5 51.15

456 89 44.5 1 44.5 95.65

457 159 79.5 1 79.5 175.15

458 243 121.5 1 121.5 296.65

459 361.2 180.6 1 180.6 477.25

460 434 217 1 217 694.25

461 490.5 245.25 1 245.25 939.5

462 510.7 255.35 1 255.35 1194.85

463 645 322.5 1 322.5 1517.35

464 761 380.5 1 380.5 1897.85

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Figure 2: Elevation - Capacity and Elevation- Area Curve

3.3 Flow Duration Curve

Twenty years of streamflow records (2009-2028) were utilized. The streamflow data was

arranged in ascending order. The percentage of exceedence and annual projected hydropower

generation potential were computed as shown in Table 4. The Flow Duration Curve as well as the

Power Duration Curve are plotted as shown in Figures 3 and 4.

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Table 4: Computation of Flow Duration Curve Using 20 years of Data

No. Year Flow(m3/s)

Flow in Ascending Order Power=9.81QHe (kw)

% of time of availability

1 2009 22.57 21.97 12789.18 100

2 2010 22.82 21.98 12795 95

3 2011 23.14 22.03 12824.1 90

4 2012 22.99 22.57 13138.45 85

5 2013 23.71 22.79 13266.51 80

6 2014 24.39 22.82 13283.98 75

7 2015 23.34 22.99 13382.94 70

8 2016 21.98 23.14 13470.26 65

9 2017 21.97 23.34 13586.68 60

10 2018 22.03 23.61 13743.85 55

11 2019 22.79 23.71 13802.07 50

12 2020 23.61 24.34 14168.8 45

13 2021 24.49 24.39 14197.91 40

14 2022 24.94 24.49 14256.12 35

15 2023 24.8 24.8 14436.58 30

16 2024 24.34 24.83 14454.04 25

17 2025 24.83 24.94 14518.07 20

18 2026 26.06 25.39 14780.03 15

19 2027 25.39 26.06 15170.05 10

20 2028 26.07 26.07 15175.87 5

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Figure 3: Ero-Omola Flow Duration Curve

Figure 4.: Ero-Omola Power Duration Curve

3333333333 3.4 Sequent Peak Algorithm Computation Input to sequent peak algorithm computation consists of hydropower water demand,

municipal water supply, irrigation water requirement, ecological water requirement, point rainfall,

evaporation and runoff. The various requirements are:

a) Hydropower Water From the flow duration curve Figure 3, 100% dependable hydropower demand flow was

estimated at 21.80m3/s. The hydropower releases for all year round generation is approximately

21.00m3/s. The yearly demand is computed thus:

Yearly demand = 24 x 3600 x 365 x 21.00 = 662.256 x 106m3

b) Municipal Water Supply Requirement Estimated total water requirement for the benefiting communities within the three LGAs

with a population of 172,207 (NPC, 2007) =46,495.89m3/day

A daily dependable release is estimated as;

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Total Annual Supply: 0.538m3/s x 24 x 60 x 60 x 365 =16.966 x 106m3

c) Irrigation Water Requirement

Gross Area =480 ha

The water requirementis:43.07m3/ha/day=20673.6m3/day =

0.24m3/s x 24 x 60 x 60 x 365 = 7.568 x 106m3 annually.

d) Ecological Water Requirement

The ecological water releases = 1.6 x 10-3m3/s x 60 x 60 24 x 30 = 4.1472 x 10-3Mm3/Month

or 50.366 Mm3/annum based on the average wash bores and tube wells recharge rate of 1.6 l/s, in

Fadama areas downstream of tailrace channels (FMWR, 2007).

The sequent peak algorithm is based on the above and data on rainfall, evaporation for the

area and was used to determine reservoir storage to meet the demand of the system for hydropower,

water supply, irrigation, ecological releases and losses. The detail computation is indicated in Table

5 and Figure 5.

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Table 5: R

eservoir Capacity Sim

ulated with Sequent Peak A

lgorithm

Ecological !release !(M

m! 3!)!

Direct R

ainfall !(M

m! 3)!

Change in !

storage Q-D!

Cum

ulative !Storage!

Reservoir !

capacity!

(Mm! 3!) (9)!

(Mm! 3!)!

X 10! 3!

(Mm! 3!)!

Jan.!16.201!

58.39!0.095!

4.147!8.4!

1.440!0.005!

44.890!44.890!

Feb.!12.371!

52.73!0.123!

4.147!6.5!

1.348!0.008!

48.689!93.579!

Mar.!

10.057!58.39!

0.147!4.147!

3.4!1.440!

0.031!43.721!

137.299!April!

33.281!56.51!

0.135!4.147!

1.5!1.394!

0.058!70.811!

208.110!May!

52.622!58.39!

0.121!4.147!

2!1.440!

0.092!87.773!

295.883!June!

55.445!58.39!

0.120!4.147!

0!1.394!

0.110!92.662!

388.544!July!

64.541!58.39!

0.091!4.147!

0!1.440!

0.082!101.712!

490.256!Aug.!

98.98!58.39!

0.086!4.147!

0!1.440!

0.070!136.144!

626.400!Sept.!

127.192!56.51!

0.092!4.147!

2!1.394!

0.138!164.344!

790.744!Oct.!

106.913!58.39!

0.100!4.147!

3.8!1.440!

0.092!140.285!

931.029!Nov.!

83.739!56.51!

0.102!4.147!

6!1.394!

0.015!116.758!

1047.787!P1!

Dec.!

53.511!58.39!

0.097!4.147!

8.6!1.440!

0.006!82.000!

-965.788!Jan.!

16.2!58.39!

0.095!4.147!

8.4!1.440!

0.005!44.889!

-920.899!Feb.!

12.371!52.73!

0.123!4.147!

6.5!1.348!

0.008!48.689!

-872.210!Mar.!

10.06!58.39!

0.147!4.147!

3.4!1.440!

0.031!43.724!

-828.486!April!

33.28!56.51!

0.135!4.147!

1.5!1.394!

0.058!70.810!

-518.677!T1!

May!

52.62!58.39!

0.121!4.147!

2!1.440!

0.092!87.771!

606.447!June!

55.45!58.39!

0.120!4.147!

0!1.394!

0.110!92.667!

699.114!July!

64.54!58.39!

0.091!4.147!

0!1.440!

0.082!101.711!

800.824!Aug.!

98.98!58.39!

0.086!4.147!

0!1.440!

0.070!136.144!

936.969!Sept.!

127.19!56.51!

0.092!4.147!

2!1.394!

0.138!164.342!

1101.311!Oct.!

106.91!58.39!

0.100!4.147!

3.8!1.440!

0.092!140.282!

1241.593!Nov.!

83.739!56.51!

0.102!4.147!

6!1.394!

0.015!116.758!

1358.351!P2!

Dec.!

53.511!58.39!

0.097!4.147!

8.6!1.440!

0.006!82.000!

900.350!

11!

Municipal !w

ater !supply!

6!7!

8!

Irrigation !W

ater !R

equirem!

ent(Mm! 3!) !

X 10! -4!

(2)+ (8) -(3)- (4)-(5)-(6)-(7) !

Month!

Monthly flow

!Q

(Mm! 3!)!

Hydropow

er !w

ater !D

emand(M

m! 3!)!

Evaporation!

(Mm! 3!)!

10!1!

2!3!

4!5!

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Figure 5: Sequent Peak Algorithm

Figure 6: Tailrace Rating Curve

Figure 7: Head Discharge Curve

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3.4 Simulation Results

The objective of simulation is to optimize potential firm energy. The simulation

procedure is presented below while the results are shown in Table 6.

(1) Critical Period (Column 1 and 2): The critical drawdown period has been defined

as the seasonal cycle between the period when the reservoir is empty and when it is

refilled to full capacity. Or the period during which all usable storage would have

been fully drafted for optimum generation. The length of the critical drawdown

period would be 29 months, (September -January)

(2) Average Streamflow (Column 3): From the flow records, the average discharge into

Ero-Omola reservoir during the critical drawdown period was found to be 21.39m3/s.

(3) Net Reservoir Evaporations Loss: Evaporation = {19.44 x 106 m2 x 150mm/1000 x

0.75} = 2.187 (Mm3) or 2.187Mm3/24x60x60x30=0.844m3/s (column 4)

(4) Consumptive Withdrawals and Demands: (Column 5). Irrigation and Water

Supply 0.24m3/s + 0.538m3/s = 0.778m3/s {section 3.4(a) and (b)}.

(5) Net Reservoir Inflow. Given the reservoir inflow in (Column 3), evaporation rate,

and reservoir withdrawal in (Column 5), then the net reservoir inflow for the same

period is Net inflow = I - E – W = 49.071+ 0.8437m3/s) – 0.778m3/s =49.137m3/s.(

Column 6).

(6) Annual Energy (Column 7), is computed as pgQHeTP = = P = 9.81 x 21 x

57.63 x 0.85 x 24 x 365 =8839272.486KWh/12 =736385.037 KWh. This value is

distributed on monthly bases in accordance to demand allocation. (Column 7)

(7) Average Pool Elevation: (Column 8). The reservoir elevation over the critical

drawdown period is approximated as 50% of the usable storage. The storage at the

top of Forebay is 1420m2 and the storage at the bottom of Reservoir is 25m2

The total reservoir storage at 50% usable storage is estimated as:

The pool elevation at 50% usable storage is found to be El.

455.21m

(8) Hydraulic Net Head: (Column 9). The net head corresponding to successive

average pool elevation in column 8 is estimated from tailwater rating curve in

Figure 6 and head discharge curve in Figure 7.

(9) Determine Required Power Discharge. (Column10). The firm energy requirement

for September, 2009 was found to be 736385.037 kWh. The required power

discharge would be computed as follows;

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This value is inserted in Column 10.

(10) Minimum Discharge for Downstream Requirement: (Column 11). Ecological

water requirement is presented in column 11 as 4.2 x 10-3m3/s. per month.

(11) Total Discharge. (Column12). The total required discharge is the sum of the power

discharge needed to meet firm energy (Q, Column 10) plus estimated leakage losses

(QL = 2.5m3/s) . If this value exceeds the required power discharge plus losses, it

would serve as the total discharge requirement. For the month of September, the

minimum discharge requirement is 26.646m3/s, so the power discharge

requirement establishes the total discharge requirement (Column 12). Qp + 2.5.

(12) Compute Change in Storage.(column 13). The change in reservoir storage is a

function of net inflow (Column 6), total discharge requirements (Column 12), at

the start-of-month, reservoir elevation (Column 16 for the previous month). The

difference between the net reservoir inflow and the total discharge requirement

would establish whether the reservoir would draft, fill, or maintain the same

elevation. This computation represents the solution of the continuity equation,

which, when rearranged, would be as follows;

(22)

For the month of September = 22.491m3/s

The value would be converted to 106m3 using the discharge-to-storage

conversation factor ( for 30-day month,

x 106m3

These values are inserted in Columns 13 and 14. For those months where net inflow

exceeds total discharge requirements, the reservoir would store the difference unless

it is already at the top of forebay pool. If the reservoir is full, the full net inflow

(minus losses) would be discharged through the powerhouse, if possible over

and above the firm energy requirement (Column 7)

(13) Compute End-of-Month Reservoir Status (Column 15). The change in storage,

, can also be expressed as follows:

where: S1=start-of-period storage volume

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S2 = end-of-period storage volume

The change in reservoir storage would be applied to the start-of-month storage

volume (Column 15) of preceding month to determine the end-of-month storage

volume. The end-of-month reservoir elevation was obtained from the storage-

elevation curve (Table 3 and Figure 2). For September, 2012;

From Figure 2, the end-of-month reservoir elevation is found to be El. 454.50m.

(14) Reservoir Elevation at the End of Critical Drawdown: (column 16): This is

obtained from the storage-elevation curve or from column 15.

(15) Compute Total Generation (Column 18): During the critical period, generation

will be limited to meeting firm energy requirements. The generation is computed by

applying the net head (Column 9) to the greater of the required power discharge or

the water quality requirement (Column 11) minus 2.5 m3/s losses. For September

2009, the generation would be:

736385.036

Which is, of course, equal to the firm energy requirement for the month of

September as calculated in step 6.

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TABLE&&6&:&Sim

ulated&Sequential&Streamflow

&Routing&for&Optim

ization&of&Potential&Hydropow

er&Developm

ent

12

34

56

78

910

1112

1314

1516

1718

S2=1858.296

MONTH

YEAR

(m3/s)

&(m3/s)

&(m3/s)

&(m3/s)

MWh

(m)

(m)

Qp(m

3/S)(m3/S)&10

3(m

3/S)&(m

3/S)&(m

cm)

&(mcm

)Elevation

&&&&&&&m2

August&

2009$$$$$$$$$$$$$%

$$$$$$$$$$$$%$$$$$$$$$$$$$%

$$$$$$$$$$$$$$$%$$$$$$$$$$$$$$$$$$$$%

$$$$$$$$$$%$$$$$$$%

$$$$$$$$$%S1=1800.00

1800461.5

1420

September

200949.071

%0.8440.778

49.137736385.037

461.549.83

24.1474.2

26.6469722.490

58.2931858.293

460.031410.79

736385.037October

200939.917

%1.0860.778

40.225442007.825

461.249.39

14.6234.2

17.12323.101

59.87959.879

459.711303.45

442007.825Novem

ber2009

32.307%1.2937

0.77832.823

442007.825461.1

49.3914.623

4.217.123

15.70040.693

1898.987459.05

1261.23442007.825

Decem

ber2009

19.979%1.1925

0.77820.394

736385.037461

49.3924.362

4.226.862

%6.469%16.767

43.113458.8

1209.17736385.037

January2010

6.0740.8437

0.7784.452

736385.037460.5

54.3622.135

4.224.635

%20.182%52.313

1846.674457.91

1176.12736385.037

February2010

3.611.0856

0.7781.746

442007.825459.01

54.3913.279

4.215.779

%14.032%36.372

6.740457.45

1125.04442007.825

March

20103.423

1.29370.778

1.351442007.825

45944.06

16.3924.2

18.892%17.541

%45.4661801.208

457.171043.76

442007.825April

201012.223

1.19250.778

10.253442007.825

458.9153.02

13.6224.2

16.122%5.869

%15.214%8.473

457.11011.19

442007.825May

201020.02

1.06870.778

18.173736385.037

458.4551.86

23.2024.2

25.702%7.528

%19.5141781.694

457975.84

736385.037June

201021.91

%0.05750.778

21.190736385.037

458.1151.19

23.5054.2

26.005%4.816

%12.483%20.956

456.02916.01

736385.037July

201025.941

%0.80440.778

25.9671473654.09

458.0152.18

46.1474.2

48.647%22.679

%58.7851722.910

455.98779.84

1473654.089August

201039.537

%0.75940.778

39.5181473654.09

457.8150.97

47.2424.2

49.742%10.224

%26.500%47.456

455.17722.51

1473654.089Septem

ber2010

45.15%0.8437

0.77845.216

736385.037457.53

49.8324.147

4.226.647

18.56948.130

1771.040454.85

709.92736385.037

October

201042.858

%1.08560.778

43.166442007.825

457.2949.39

14.6234.2

17.12326.042

67.50220.046

454.67678.45

442007.825Novem

ber2010

33.2421.2937

0.77831.170

442007.825457.29

49.3914.623

4.217.123

14.04736.410

1807.450454.32

643.26442007.825

Decem

ber2010

19.8521.1925

0.77817.882

736385.037457.17

49.3924.362

4.226.862

%8.981%23.278

%3.231454.12

601.57736385.037

January2011

6.10.855

0.7784.467

736385.037457

54.3622.135

4.224.635

%20.168%52.275

1755.176453.81

575.18736385.037

February2011

3.9570.855

0.7782.324

442007.825456.41

54.3913.279

4.215.779

%13.455%34.875

%38.106453.48

534.07442007.825

March

20113.122

0.8550.778

1.489442007.825

456.2144.06

16.3924.2

18.892%17.403

%45.1091710.067

453.11492.11

442007.825April

201111.635

0.8550.778

10.002442007.825

456.1353.02

13.6224.2

16.122%6.120

%15.863%53.969

453448.78

442007.825May

201120.399

0.8550.778

18.766736385.037

455.9651.86

23.2024.2

25.702%6.936

%17.9781692.089

452374.13

736385.037June

201122.441

%0.8550.778

22.518736385.037

455.3451.19

23.5054.2

26.005%3.487

%9.039%63.009

451.94328.19

736385.037July

201127.927

%0.8550.778

28.0041473654.09

455.0552.18

46.1474.2

48.647%20.643

%53.5061638.584

451.81269.11

1473654.089August

201140.677

%0.8550.778

40.7541473654.09

45550.97

47.2424.2

49.742%8.988

%23.297%86.306

451.65233.14

1473654.089Septem

ber2011

41.542%0.855

0.77841.619

736385.037454.86

49.8324.147

4.226.647

14.97238.808

1677.391451.57

183.62736385.037

October

201146.015

%0.8550.778

46.092442007.825

454.2149.39

14.6234.2

17.12328.969

75.087%11.219

451.39151.41

442007.825Novem

ber2011

34.204%0.855

0.77834.281

442007.825453.73

49.3914.623

4.217.123

17.15844.473

1721.864451.28

92.56442007.825

Decem

ber2011

19.725%0.855

0.77819.802

736385.037452.11

49.3924.362

4.226.862

%7.060%18.300

%29.518451.25

41.87736385.037

January2012

6.125%0.855

0.7786.202

736385.037451.91

54.3622.135

4.224.635

%18.433%47.778

1674.087451

25.33736385.037

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%SU

M701.983

3.85927.562

670.56220771722.73

132661481

666.448132.8

750.947%59.966

%155.43226125.049

20771715.732AVERAG

E23.399

0.1280.919

22.353692390.758

442.1949.38

22.9814.427

25.031%2.068

%5.360900.864

716266.0602=&YEA

R3=&IN

FLOW

5=WITH

DRA

WALS

9=NET[H

EAD10=REQ

UIRED

&PEAK&D

ISCHARG

ES

11=ECOLO

GICA

L&WATER&RELEA

SES13=CH

ANGE&IN

&&STORA

GE(Δ

S)&(m3/S)

16&=&ElEVATIO

N18=TO

TAL&PO

WER&G

ENERA

TIONS

15=END&OF&PERIO

D&OF&&RESERV

OIR&STO

RAGE&(S2)

17=&RESERVOIR&SU

RFACE&A

REA

RI

END&OF&CRITICA

L&PERIOD

START&O

F&CRITICA

L&PERIOD

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

8=AVERA

GE&PO

OL&ELEV

ATIO

N

12=TOTA

L&DISCH

ARG

E&&FOR&&D

OWNSTREA

M&REQ

UIRM

ENT

14=&EQUIVALEN

T&CHANGE&IN

&STORA

GE&(Δ

S)&(mcm

)&

4=EVAPO

RATIO

NS

RI=&ROUTIN

G&PERIO

D/IN

TERVAL

6=NET[IN

FLOW

7=ENERG

Y&REQUIREM

NT

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42!

16. Summary

The simulation was carried out on ‘excel’ with the above items as input. The reservoir

simulation was based on the initial estimate of reservoir capacity of 1812 x 106m3 at 2.7 x 103m3/s

maximum inflow and dead storage of 1.8075 x 106m3. The initial analytical estimates of potential

hydropower was estimated at 8.01101MW, while annual generation potentials was estimated at

14035.272 MWh at hydraulic capacity of 21m3/s.

The simulation result given in Table 6 however show that the potential power could be

higher i.e P= 9.81 x 21 x 57.63 x 0.85 =10.091 MW while the annual energy of =18,401.56501

MWh was reached.

Hence the result indicated about 20.6% more potential hydropower, while annual energy

was increased by additional 23.4%.

4 Conclusion

The major conclusions derived from the study are:

a) The theoretical potential hydropower generating capacity of Ero-Omola fall at 100%

dependable flow of 80 years return period is estimated at 8.011MW. The annual average

energy is estimated at 14035.272MWh.

b) The simulated potential hydropower generating capacity of Ero-Omola fall at 100%

dependable flow of 80 years return period is estimated at 10,091.502MW. The annual

average energy is estimated at 18,401.56501MWh

c) The simulation result indicated about 20.6% for more potential hydropower, while annual

energy was optimized by 23.4%.

d) Water treatment plant capacity is estimated at 22,500 litres or 22.5m3/s.

e) Irrigation water requirement is estimated at 2.2 x 106m3 with peak irrigation water demand

of 43.07m3/ha/day.

f) The minimum ecological water requirement downstream is estimated at 1.6 x 10-3m3/s,

which would minimize or eliminate seasonal flooding downstream.

References

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43!

1. C. Punmia, and M. Pande, "Runaway potential: Small hydro in Europe and beyond".

Renewable Energy World, pp. 248-253. July-August, 2008,

2. Department of Army Corps of Engineer, "Hydropower Design Manual", Vol.3, No, 125,

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